Purpose: The purpose of this paper is to understand the gender differences in the formation of entrepreneurial intentions among future communications professionals. Building on the Theory of Planned Behavior (TPB), it analyzes the relationships between the variables of personal attitude towards entrepreneurship (AE), perceived behavioral control (PBC) and the influence of the social environment of entrepreneurs on their entrepreneurial intention (EI).

Design/methodology:This empirical research is based on a non-random convenience sample consisting of 234 students enrolled in the final courses of the journalism degree program. The models have been tested according to the PLS (Partial Least Square) method.

Findings:The results indicate the existence of explanatory models of different entrepreneurial intentions for men and women. In this regard, the significant relationship between social norms and social assessment in the entrepreneurial intention of women is important.

Research limitations/implications: This study analyzes communications students, and although the theory of planned behavior is quite strong, the results cannot be generalized to sector professionals.

Practical implications:Research like this helps identify the background on which to act and to be developed in the training programs of future communicators. From the point of view of research, this study reveals the usefulness of TBP.

Social implications:Improved employability of professionals in the communications sector, with attention to the differences between men and women when considering entrepreneurship as a career option.

Originality/value:This is the first study of its kind conducted in the context of communications and with university students, specifically, those pursuing a degree in communications, who are faced with an economic crisis and a changing environment, in which entrepreneurship is critical to their professional development.

The emergence of digital technology in all spheres of the communications sector (production, distribution and consumption) is generating drastic changes in the mass media (Jarvis, 2015). This has led to many communicators being compelled to engage in the informative activity on their own account, either as freelancers or by creating their own media.

In Spain, the impact of these transformations has been particularly harsh. According to the Annual Report of the Journalism Profession edited by the Madrid Press Association (APM) (Palacios, 2015), between 2008 and 2015, a total of 12,200 jobs have been destroyed and 375 media companies have closed their doors. Similarly, labor conditions have worsened: the average base salary for communications professionals covered by a collective bargaining agreement has been reduced by 17% since 2010, and 25% of freelance journalists have experienced a 70% decline in their income.

As a result, journalists believe that the two main problems faced by the profession are “increased unemployment and job instability” and “the poor compensation for journalistic work.” If the labor conditions of female journalists are analyzed, it can be seen that 62.5% of those hired earn less than €1000, as compared to 46.4% of men. A glass ceiling also exists, which serves as a barrier to executive positions; only 15.9% of these positions are held by women, a percentage which has held steady over time since before the crisis (Caro-González, García-Gordillo, Rodríguez-Rad & Jiménez-Marín, 2007).

In this context, one third of the journalists indicate that they have been forced to do freelance work (Palacio, 2015). It would appear that most of these freelancers are women, as the precarious labor conditions are an incentive for self-employment (Dyer, 1994). Creating their own business would allow them to break through the glass ceiling, accessing more equal pay and executive positions in the organizations. However, the aforementioned report from the Madrid Press Association (Palacio, 2015) indicates that only 40.3% of freelance workers are women. This figure does not seem to make sense if we take into consideration that between 2011 and 2014 a total of 15,807 journalists earned their degrees in Spain, of whom more than 65% are women. This information is in line with the data from the GEM (Global Entrepreneurship Monitor) report for Spain (Peña et al., 2016, pp. 126), where 58.5% of the new and fledgling entrepreneurs are men.

In order to understand the reasons for the lower rates of entrepreneurship in women, we must ask ourselves whether there are any differences in the variables explaining it. Discovering these differences can help to design programs of incentives and training in entrepreneurship that improve the ratio of the participation of women in entrepreneurial activities (Díaz-García& Jiménez-Moreno, 2010).

Researchers pay attention to entrepreneurial intention because it is a predictor of behavior. Martínez, Mira and Gómez (2010) and Ventura and Quero (2013) consider the understanding of entrepreneurial intention to be very relevant in order to reveal the reasons for the lower rates of entrepreneurship in the female population. Entrepreneurs are characterized by their ability to detect opportunities in their surroundings and to innovate in order to take advantage of them. This process is intentional, and thus the development of this intention can be considered the first step towards the creation of a new company (Crant, 1996; Krueger &Carsrud, 1993; Lee & Wong, 2004). An increase in entrepreneurial intention would subsequently lead to an increase in entrepreneurship (Ajzen, 2005).

The consideration of gender in this field reveals contradictory results. Part of the researchers do not consider it to be very important when explaining the intention to found a business (Armitage & Conner, 2001; Pruett, Shinnar, Toney, Llopis& Fox, 2009). They believe that the gender of the person has no influence on their intention to engage in entrepreneurship, and is used as a control variable.

However, there are other researchers who argue that the influence of gender is not noticeable because the methodological and theoretical approaches are inappropriate and, therefore, the influence of gender on entrepreneurial intention has not been studied in depth and requires further study before any final conclusions can be reached (Shay &Terjesen, 2005; Shook &Bratianu, 2010; Kobeissi, 2010). The indirect effect of gender on entrepreneurial intention is explained in few studies (Kickul, Krueger &Maxfield, 2005; Wilson, Kickul&Marlino, 2007; Goyanes, 2015).

With this study, we wish to contribute new empirical evidence on the topic, analyzing the entrepreneurial intention from the perspective of gender in the case of journalism students. The Theory of Planned Behavior (TPB) is used to better understand the extent to which gender influences entrepreneurial intention (EI) and its antecedents. This theory is the model most commonly used to study entrepreneurial intentions (Arias, Restrepo&Restrepo, 2016), and it has provided generally accepted results, explaining an amount of variance in EI ranging from 0.27 to 0.65 (Armitage & Conner, 2001; Ajzen, 2005).

The TPB model was tested on a population of 234 students in the final years of the journalism degree program. The results are obtained from structural equation models analyzed using the PLS program.

The article is structured as follows: first, the Planned Behavior Theory model is described that is used as the basis for the study;next, the methodology used is explained, namely the PLS (Partial Least Square) method; finally, the results are reported and contrasted with the previous literature. This work ends with a discussion of the most important theoretical and methodological contributions and their implications to the training of future journalism professionals in entrepreneurship.

2.Theoretical framework

To find out the impact of gender on the intention to engage in entrepreneurial activities by future professional journalists, the Theory of Planned Behavior (TPB) is used (Ajzen, 1991). The basic premise of this theory is that there is a strong link between the intention to act and real behavior. Armitage and Conner (2001), in a meta-analysis of 185 research studies using the TPB model, demonstrated that this theory could explain 27% of the variance in behavior and 39% of the entrepreneurial intention.

The literature on entrepreneurial intention (EI) clearly shows the usefulness of TPB in demonstrating that there is a link between the antecedents of the EI, the intention itself and behavior (Krueger, Reilly &Carsrud, 2000; Guerrero, Rialp&Urbano, 2008).

The TPB model can be seen in Figure 1. The dependent variable is the entrepreneurial intention (EI) and the independent variables are the attitude towards entrepreneurship (AE), the perceived behavioral control (PBC), social norms (SN) and social evaluation (SE).

Entrepreneurial intention (EI) constitutes the key to understanding the entrepreneurial process. “A person develops the intention to perform a certain behavior; this intention remains as a predisposition until, when the appropriate time and opportunity come, the intention is transformed into an action” (Ajzen, 2005). In our case, EI represents a construct that connects the process of detecting an opportunity with actually carrying it out (Dimov, 2007; Carsrud&Brännback, 2011). This variable is one of the most viable precursors of entrepreneurial behavior, which will lead to the creation of new businesses (Prodan&Drnovsek, 2010).

Perceived behavioral control (PBC) is another latent variable that plays an important role in predicting EI and entrepreneurial behavior in communications. This construct reflects the perception of the ability an individual has to create and manage a new business (Jaén, 2010). Researchers vary in their use of the term and often use PBC interchangeably with self-efficacy, or add small nuances that differentiate between these terms (Krueger et al, 2000). Authors such as Armitage and Conner (2001) and Pruett et al. (2009) found a significant link between PBC and EI. However, in the multicultural work of Engle et al. (2010), it was observed that the relationship between PBC and EI was only significant in seven of the twelve countries studied. It therefore continues to be interesting to study this relationship in different contexts, such as the unique case of journalism students in Spain.

In any case, the PBC construct is among the strongest predictors of EI, along with AE, and it is repeatedly used to explain EI (Ajzen, 2005).

The attitude towards entrepreneurship (AE) constitutes the third construct of the model. It is a personal factor that indicates the individual’s desire to create value by exerting entrepreneurial behavior (Fini, Grimaldi, Marzocchi&Sobrero, 2012). The positive, direct correlation with EI has been established in different studies (Engle et al., 2010; Liñán, Rodríguez-Cohard& Rueda-Cantuche, 2011).

Other constructs that help understand the antecedents of entrepreneurial intention are social norms (SN) and social evaluation (SE). It is a matter of finding out the extent to which an individual’s environment influences his or her behavior when engaging in entrepreneurial activities (White, Smith, Terry, Greenslade&McKimmie, 2009). If the social environment values the business activity and it is believed that the individual has the necessary knowledge and skills, theywill be more motivated and feel capable of starting a business (GallurtPlá, 2010).

In this case, the influence on the future entrepreneur depends on his or her parents, friends and other people who can somehow promote or disapprove of the idea of entrepreneurship. Some studies confirm that the social norms directly affect EI (Pruett et al., 2009; Engle et al., 2010). However, Shook and Bratianu (2010) found a negative relationship between context norms and EI. Krueger et al. (2000) and Armitage and Conner (2001) also reported a weak relationship between the two variables. In this sense, it is interesting to refer to other studies that contribute to clarifying this debate.

Finally, Ajzen (2005) and Guerrero, Lavin and Álvarez (2009) found an indirect effect of the social norms and assessments on EI with the mediation of AE and PBC. Social pressure tends to promote a favorable attitude towards entrepreneurship and can also increase the PBC, thus impacting the EI. Zahra, Gedajlovic, Neubaum and Shulman (2009) consider the impact of culture to be decisive, as defined through social evaluation and social norms in business behavior.

As observed, in spite of the support received in the literature, the results of the works that use TPB do not always coincide. Along these lines, while Gird and Bagraim (2008) indicated a significant relationship among the three antecedents of EI and the intention to start a business, Liñán and Chen (2009) demonstrated that there is no link between EI and social norms, corroborating the previous findings of Krueger et al.(2000). Engleet al. (2010), in their study with samples from twelve countries, found that in half of them, the predictors of EI were social norms and the desire to engage in entrepreneurship, while in the other half, they were social norms and perceived behavioral control.

The repercussion of this latter work points in the direction of carrying out more specific studies using TPB, instead of trying to identify universal models. Research studies are very homogeneous and have not taken into account contextual factors (Elfving, 2008; Kickul, Gundry, Barbosa &Whitcanack, 2009). Furthermore, as indicated by Alonso-García (2012), a large part of the studies are based on data collected in the United States and there are, with a few exceptions, not many international works that compare different social and cultural environments (De Pillis& Reardon, 2007; Delmar &Davidsson, 2000; Liñán& Chen, 2009). With this study, the intent is to contribute evidence on the TPB model applied to entrepreneurship in the specific sector of communications.

3.Objectives and hypothesis

The aim of this study is to analyze the entrepreneurial intention of journalism students from the perspective of gender and within the framework of Planned Behavior Theory. This will enable us to test the validity of the model in the case of journalism students and identify significant differences in the model, according the gender of the person surveyed.

As described in the theoretical framework, the TBP model measures entrepreneurial intention (EI) based on the variables perceived behavioral control (PBC) and attitude towards entrepreneurship (AE). This proposal is enriched by two antecedents: on the one hand, social norms (SN), and on the other, the social evaluation of entrepreneurship (SE).

The TBP model that will be analyzed is shown in Figure 1.

Figure 1. Proposed model and hypotheses

According to the previous theoretical analysis, the following hypotheses are proposed:

H1: PBC is positively related to EI.

H2: AE is positively related to EI.

H3: SN is positively related to PBC.

H4: SN is positively related to AE.

H5: SN is positively related to EI.

H6: SE is positively related to PBC.

H7: SE is positively related to AE.

H8: SE is positively related to EI.

Similarly, if the gender of the students is taken into account, differences can be expected between the models explaining entrepreneurial intention.

4.Methodology, analysis and results

This empirical research is based on a non-random convenience sample. In particular, the data were collected through a questionnaire linked to the Facebook page of the business creation courses in the College of Communications at the University of Seville. The universe of students is a very commonly used context in this type of research (Krueger et al., 2000; Lüthje& Franke, 2003; Fayolle&Gailly, 2004; Souitaris,Zerbinati& Al-Laham, 2007; Ventura &Quero, 2013). The literature has evidenced several reasons that back the use of this population to analyze entrepreneurial intentions (Arias et al., 2016). Among them is the fact that university students will soon have to make a decision about their professional future, and therefore statements about their intentions are premeditated (Liñán& Santos, 2007). Consequently, they constitute a potentially entrepreneurial group (Sánchez, Lanero&Yurrebaso, 2005) that is considered to be representative of the population in order to analyze human behavior (Harrison & List, 2004).

The questionnaire was administered at the start of the courses to all students registered during the academic years 2013-14, 2014-15 and 2015-16. The final number of students surveyed, once the invalid surveys were eliminated, was 234. The gender composition of this sample is in accordance with that of the universe explored (69.27% female students and 30.73% male students).

The questions on the questionnaire were obtained from scales previously tested in different studies. In particular, the questionnaire used by Sahinidis,Giovanis and Sdrolias(2012) was adapted, which was constructed based on the instruments created by Liñán and Chen (2009) and Guerrero et al.(2009).

The reasons for using PLS instead of other types of statistics modeling programs with structural equations are (Diamantopoulos &Winklhofer, 2001; Rigdon, 2016):

•the exploratory nature of this work;

•PLS does not require large samples, as opposed to other statistics programs (AMOS, EQS, etc.), to obtain results;

•PLS is a non-parametric technique, and therefore it is not necessary to ensure a normal data distribution.

The proposed model was assessed for each group, i.e., women (G1) and men (G2).

A structural equation model is described by two models:

•a model of measurement between the manifest variables (MVs) and their own latent variables (LVs) and

•a structural model of the relationships between the endogenous and exogenous variables.

Figures 2 and 3 show the model in G1 and G2, once the PLS algorithm has been applied (Ringle, Wende& Will, 2005) and the indicators have been removed that have a lambda coefficient of less than 0.7 in either model (pa1, sn3, sv3, pbc1, pbc4, pbc5). This ensures that the shared variance between the construct and its indicators is greater than the variance due to error (Carmines &Zeller, 1979).

Therefore, the resulting model that is valid for both G1 and G2 would be:

The reliability and validity of the measurement models were determined prior to the analysis of the structural model. The individual reliability of each indicator was evaluated by examining the loads (λ) or simple correlations with their respective latent variables (LV). The indicators were accepted when λ ≥ 0.707. Furthermore, the indicators needed to be more strongly correlated with their own construct than with any other (Fornell&Larcker, 1981).

Table1 shows the results of the cross loading procedure for Group 1 and Group 2.

G1 Women

G2 Men

AE

CCP

SE

IE

NS

AE

CCP

SE

IE

NS

ei1

0.420

0.498

0.163

0.753

0.297

-

-

-

-

-

ei2

0.654

0.365

0.180

0.868

0.375

0.667

0.32

0.069

0.817

0.173

ei3

0.722

0.425

0.160

0.902

0.299

0.639

0.227

0.012

0.856

0.4

ei4

0.675

0.414

0.195

0.914

0.248

0.507

0.302

0.016

0.867

0.277

ei5

0.654

0.467

0.139

0.896

0.243

0.589

0.336

0.024

0.866

0.209

pa1

-

-

-

-

-

0.701

0.176

0.11

0.52

0.15

pa2

0.805

0.184

0.248

0.562

0.256

0.774

-0.095

0.268

0.514

0.414

pa3

0.821

0.222

0.271

0.599

0.256

0.787

-0.107

0.072

0.532

0.437

pa4

0.853

0.358

0.24

0.585

0.241

0.858

0.049

0.186

0.583

0.283

pa5

0.817

0.454

0.161

0.653

0.248

0.867

0.221

0.137

0.683

0.248

pbc1

0.405

0.762

0.191

0.389

0.178

-

-

-

-

-

pbc2

0.259

0.813

0.173

0.410

0.155

-

-

-

-

-

pbc3

0.340

0.855

0.215

0.472

0.144

0.039

0.785

-0.079

0.248

-0.152

pbc4

0.235

0.825

0.248

0.298

0.065

0.101

0.852

-0.053

0.257

-0.323

pbc5

0.248

0.755

0.195

0.274

0.01

-0.057

0.83

-0.12

0.23

-0.211

pbc6

0.285

0.805

0.114

0.473

0.074

0.088

0.754

-0.117

0.381

-0.016

sn1

0.222

0.167

0.238

0.290

0.866

0.356

-0.226

0.33

0.27

0.883

sn2

0.307

0.078

0.404

0.295

0.886

0.246

-0.138

0.28

0.25

0.847

sn3

-

-

-

-

-

0.338

-0.175

0.242

0.244

0.728

sv1

0.122

0.094

0.716

0.060

0.277

0.192

-0.069

0.899

0.074

0.301

sv2

0.297

0.251

0.966

0.214

0.353

0.153

-0.134

0.882

-0.012

0.32

Table 1. Results of the cross loading procedure for Groups 1 and 2

The reliability of the LV indicates the precision with which the observed variables measure it. The combined reliability was used as the reliability index for the LVs (LVs were accepted when α> 0.7). The convergent validity of the LVs was evaluated by examining the average variance extracted (AVE); see Fornell and Larcker (1981) (AVEs> 0.5 were accepted). Table 2 shows the combined reliability, the AVE and Cronbach’s alpha for each LV. The latter is adequate in all constructs in the case of Group 2. In Group 1, the constructs SE and SN are very close to 0.7, which is considered an acceptable value (George &Mallery, 2003, pp.231).

G1 Women

G2 Men

Combined

reliability

AVE

Cronbach’s alpha

Combined

reliability

AVE

Cronbach’s alpha

AE

0.894

0.679

0.842

0.898

0.640

0.858

PBC

0.916

0.645

0.891

0.881

0.650

0.820

SE

0.836

0.723

0.677

0.884

0.793

0.739

EI

0.939

0.755

0.918

0.913

0.725

0.874

SN

0.869

0.768

0.698

0.861

0.676

0.757

Table 2. Combined reliability and AVE

The discriminant validity of the latent variables was tested, analyzing whether the square root of the AVE for each LV was greater than the correlations with the rest of the LVs (see Table 3).

G1 Women

G2 Men

AE

CCP

SE

IE

NS

AE

CCP

SE

IE

NS

AE

0.824

0.8

CCP

0.373

0.803

0.058

0.806

SE

0.278

0.232

0.85

0.194

-0.113

0.89

IE

0.729

0.493

0.192

0.869

0.711

0.348

0.036

0.852

NS

0.304

0.138

0.37

0.334

0.876

0.389

-0.224

0.348

0.312

0.822

Table 3. LV correlations for Groups 1 and 2 (elements in diagonal are the square roots of the AVE)

In addition, the heterotrait-monotrait (HTMT) ratio was calculated, which detects the lack of discriminant validity (Table 4) better than the cross loading examination and the Fornell-Larcker criterion (Henseler, Ringle&Sarstedt, 2015). The HTMT ratio must be below 0.85 (Kline, 2011).

G1 Women

G2 Men

AE

CCP

SE

IE

NS

AE

CCP

SE

IE

NS

AE

CCP

0.42

0.194

SE

0.32

0.276

0.243

0.163

IE

0.818

0.538

0.2

0.813

0.41

0.093

NS

0.394

0.181

0.524

0.421

0.468

0.27

0.464

0.381

Table 4. Heterotrait-monotrait (HTMT) ratio for Groups 1 and 2

The previous works on which this study is based (Sahinidis et al., 2012; Liñán& Chen, 2009; Guerrero et al., 2009) obtained similar results from the validation of the measurement scale of the model. Specifically, they achieved a Cronbach’s alpha higher than 0.7 and the measurement variables were strongly correlated with the constructs to which they belonged.

4.3. Structural Model Analysis

After checking the validity and reliability of the measurement model, the relationships between the constructs were tested. The hypotheses were tested by examining the path coefficients (β) and their levels of significance (they were accepted when β> = 0.2). Bootstrapping was carried out with 500 sub-samples in order to check the statistical significance of each of the path coefficients. The explained variance (R2) in the endogenous LVs and the regression significance coefficient (F-test) serve as indicators of the explanatory capacity of the model.

G1 Women

G2 Men

Original Sample(O)

Sample Mean(M)

Standard Deviation(STDEV)

T Statistics

(|O/STDEV|)

P Values

Original Sample(O)

Sample Mean(M)

Standard Deviation(STDEV)

T Statistics

(|O/STDEV|)

P Values

AE -> IE

0.611

0.613

0.05

12.325

0.000*

0.644

0.642

0.089

7.241

0.000*

CCP -> IE

0.268

0.272

0.058

4.623

0.000*

0.337

0.34

0.09

3.732

0.000*

SE -> AE

0.192

0.196

0.081

2.37

0.018*

0.067

0.087

0.133

0.505

0.614

SE ->CCP

0.21

0.22

0.086

2.436

0.015*

-0.039

-0.03

0.165

0.238

0.812

SE -> IE

-0.094

-0.096

0.055

1.724

0.085

-0.112

-0.112

0.077

1.456

0.146

NS -> AE

0.233

0.244

0.094

2.47

0.014*

0.365

0.365

0.146

2.495

0.013*

NS ->CCP

0.060

0.063

0.098

0.608

0.543

-0.21

-0.21

0.191

1.1

0.272

NS -> IE

0.147

0.142

0.063

2.319

0.021*

0.176

0.176

0.101

1.733

0.084

*Significant relationships (p≤0.05)

Table 5. Results of the PLS analyses for G1 and G2

In can be seen in Table 5 that the following relationships are significant:

AE -> EI in both cases.

PBC -> EI in both cases.

SE -> AE, only in G1.

SE -> PBC, only in G1.

SN -> AE in both cases.

SN -> EI, only in G1.

The explained variance for each variable in both groups is shown in Table 6:

R Square

G1 Women

G2 Men

AE

0.124

0.155

CCP

0.057

0.052

IE

0.608

0.626

Table 6. Explained variance (R2) in endogenous LVs

With these results, the hypotheses H1, H2, H4, H5, H6 and H7 are supported for Group 1 and the hypotheses H1, H2 and H4 are confirmed for Group 2.

As a result, we can establish that the TBP model would be as follows (see Figure 4):

Figure 4. Final TPB model

5.Conclusions

The Planned Behavior Theory model is a useful tool to explain the entrepreneurial intention of journalism students who lack business training. Most existing studies on this topic have analyzed these constructs in students registered in degree programs related to the business world (Sagie &Elizur, 1999; DeMartino&Barbato, 2002; Krueger et al., 2000; Gatewood, Shaver, Powers & Gartner, 2002; Lüthje& Franke, 2003; Liñán, Rodríguez-Cohard& Rueda-Cantuche, 2005; Wilson et al., 2007; Zhao,Seibert & Hills, 2005; Sahinidis et al., 2012; Wurthmann, 2014). Moreover in this case, these are students who are faced with a context of economic crisis and change, where entrepreneurship is essential for their career development. The robustness of the TBP model has been verified in order to explain the entrepreneurial intention of the future communications professionals, both in the case of men and women, with an explained variance of 0.626 and 0.608, respectively.

The measurement model and structural model are valid. However, differences are evident in terms of the significant relationships between constructs, revealing that in the case of women, the exogenous variables SN and SE have both a direct (SN) and indirect (SN and SE) impact on the entrepreneurial intention, which is something that does not occur in the case of men, where the entrepreneurial intention is only indirectly impacted by SN. The literature review shows the opposite results; there are studies indicating that no direct relationship can be established between the subjective norms and the entrepreneurial intention (Krueger et al., 2000), while others demonstrate that said relationship does exist, and it is positive (Kolvereid&Isaksen, 2006). It may be that the response to this controversy can be found in the gender of the population surveyed. Different studies indicate that there is an important relationship between gender and EI (Farrington, Venter &Louw, 2012; Gird &Bagraim, 2008; Engle et al., 2010;Sahinidis et al., 2012;Goyanes, 2015). More specifically, some of the studies that found that environmental factors barely had any influence on men, but they did affect women (Leroy, Maes, Sels, Debrulle&Meuleman, 2009) are reinforced. In this regard, González-Serrano, Valantine, Campos, Berenguer, Moreno and Hervás(2016) observed that female physical activity and sports sciences students assess the social norm with a higher score than men. In the case of male journalism students, the relationships with one of the environmental variables were not significant.

The perception that women have, as future journalism professionals, regarding the assessment of the entrepreneurial activity by their closest environment directly and indirectly affects the intention to create a new business. The indirect impact of this perception is through the AE. In other words, women perceive that it is more attractive to create their own company if they believe that their immediate environment looks favorably upon entrepreneurial activity. This may be due to lower self-esteem that causes them to search for support beyond the perception of their own abilities. As a matter of fact, SN (assessment of entrepreneurship of the survey taker by people close to her) significantly influences, both directly and indirectly, the EI. We have found differences with regard to this point in the study by Sahinidis et al. (2012), which indicated that the environmental variables were related to both AE and PBC. It would be interesting to continue to investigate whether this difference is related to the professional orientation of the students studied or due to sociocultural aspects.

It has been concluded that entrepreneurship in the communications sector continues to be a male activity, in a masculine profession (Djerf-Pierre, 2007), where men need less approval from their environment, given that it is assumed that they can and should engage in entrepreneurial activities; however, in the case of women, it is necessary to reinforce the attractiveness of entrepreneurship with the support of their immediate environment.

More studies along these lines are necessary in order to identify the skills and competences that influence the entrepreneurial behavior of women. It is likely that variables such as confidence and self-esteem with regard to entrepreneurship are limiting the entrepreneurial capacity of women who seek approval from their environment to develop entrepreneurial behaviors. Instructors must attempt to transmit the attractiveness of entrepreneurship to female entrepreneurs.

6.Implications

It would seem, as most studies have indicated, that the long-term solution to reduce the gender differences involves modifying the educational system (Sahinidis et al., 2012). Studies like this one help identify the antecedents on which to act and that must be developed in training programs for future communications professionals. From a methodological perspective, this study reveals the usefulness and validity of the tested model. At the same time, it is considered necessary to conduct qualitative studies that make it possible to incorporate new indicators measuring constructs, such as SN and SE, which currently have few. Along similar lines, it is necessary to delve more deeply into gender differences, studying the inclusion of variables such as the existence of reference values, the labor situation of mothers and institutional support. Finally, researchers are encouraged to conduct studies focused on more specific professional populations, which would contribute to understanding the phenomenon of entrepreneurial intention in other areas in which the training program does not include contents related to the business world.

Following the proposals of BarNir, Watson and Hutchins (2011), it is necessary to introduce in the teaching-learning processes of journalists dynamics in which success stories of female entrepreneurs in communications are presented, demonstrating that getting started in a business venture does not need to be a professional career option open exclusively to men (Brito, Cruz & Hernández, 2014).

7.Limitations of the study

This study has two limitations. On the one hand, there is the fact that the entrepreneurial intention is measured statically. It would be very enriching to be able to follow a target population of study and find out what entrepreneurship is like throughout the subjects’ professional careers. In other words, this would represent taking the step from intention to action. Furthermore, the fact that this study considered journalism students means that while Planned Behavior Theory is relatively solid, it cannot be generalized to other professionals in the sector. The data must be interpreted as an experiment, something that explains the entrepreneurial behavior in a specific context. In any case, the research is relevant due to the contribution it makes to metatheoretical studies on the topic and its integration intothe conclusions of previous studies and the introduction of structural equations in studies on journalism.

Guerrero, M., Lavín, J., &Álvarez, M. (2009). The role of education on start-up intentions: A structural equation model of Mexicanuniversitystudents. In 35th annualconferenceproceedings of the Association for Small Business and Entrepreneurship.

Sahinidis, A.G., Giovanis, A.N., &Sdrolias, L. (2012). The role of gender on entrepreneurial intention amongstudents: An empirical test of the theory of plannedbehaviour in a Greek university. International Journal on Integrated Information Management, 1(1), 61-79.https://doi.org/10.15556/IJIIM.01.02.005

Shook, C.L., & Bratianu, C. (2010). Entrepreneurial intent in a transitionaleconomy: An application of the theory of plannedbehavior to Romanianstudents. International Entrepreneurship and Management Journal, 6(3), 231-247. https://doi.org/10.1007/s11365-008-0091-2

White, K.M., Smith, J.R., Terry, D.J., Greenslade, J.H., &McKimmie, B.M. (2009). Social influence in the theory of plannedbehaviour: The role of descriptive, injunctive, and in‐group norms. British Journal of Social Psychology, 48(1), 135-158. https://doi.org/10.1348/014466608X295207

Guerrero, M., Lavín, J., &Álvarez, M. (2009). The role of education on start-up intentions: A structural equation model of Mexicanuniversitystudents. In 35th annualconferenceproceedings of the Association for Small Business and Entrepreneurship.

Sahinidis, A.G., Giovanis, A.N., &Sdrolias, L. (2012). The role of gender on entrepreneurial intention amongstudents: An empirical test of the theory of plannedbehaviour in a Greek university. International Journal on Integrated Information Management, 1(1), 61-79.https://doi.org/10.15556/IJIIM.01.02.005

Shook, C.L., & Bratianu, C. (2010). Entrepreneurial intent in a transitionaleconomy: An application of the theory of plannedbehavior to Romanianstudents. International Entrepreneurship and Management Journal, 6(3), 231-247. https://doi.org/10.1007/s11365-008-0091-2

White, K.M., Smith, J.R., Terry, D.J., Greenslade, J.H., &McKimmie, B.M. (2009). Social influence in the theory of plannedbehaviour: The role of descriptive, injunctive, and in‐group norms. British Journal of Social Psychology, 48(1), 135-158. https://doi.org/10.1348/014466608X295207